Evaluation Method of Public Transportation System Based on Fuzzy Cloud Model

Introduction

Public transportation system is bound up with various aspects of cities’ development, and it has a direct impact on people’s travelling. Moreover, public transportation system evaluation is the basis for designing the distribution of urban public transportation, and the evaluation is also an important guide for the development of cities’ transportation.

A method called fuzzy comprehensive evaluation based on DEA model (Fu & Jin, 2010), in which the fuzzy evaluation and data envelopment analysis was combined. Fu tried to indicate the fuzziness by fuzzy evaluation.as people judging the qualitative things. However, the accuracy of fuzzy evaluation’s discriminant function itself is contrary to human mind. Evaluation model of urban public transportation based on structural equation (Liu & You, 2013), which has made use of the data from a questionnaire to modify model. It has analyzed the relation and influence between the different indexes with strong explanatory, which can offer support for decision. However, it is obvious that questionnaires which use accurate figure to represent evaluation result fail to demonstrate the fuzzy evaluation as how we human beings judge the fuzzy things. Then, with the congestion intensity index acting as the breakthrough of high speed congestion (Lee J.,2014), the paper uses fuzzy logic to evaluate transportation system comprehensively, and the design has set up microscopic traffic flow model based on the control theory firstly. Research on congestion characteristics based on velocity distribution (Ko & Guensler, 2005) by statistical method of gauss mixture distribution has two kinds of traffic conditions: Identify congestion and non-congestion by, it has indicated the practical traffic application of this model. Then the current situation and trend of congestion in American cities has been introduced (Hallenbeck, 2005). In another literature, the cloud model is used to make the real-time judgment of the traffic jam (Gao & Xu, 2013), they have taken various factors into consideration and made use of the cloud model to evaluate different indexes, it failed to consider the concrete proportion of different indexes.

This paper firstly gains the proportions of the indexes by comprehensive evaluation and analysis based on analytic hierarchy process (AHP). Then, it extracts the index principal component and obtains the membership function by fuzzy evaluation. Thirdly, it absorbs the main idea of importing membership function into cloud to construct the non-uniform unilateral cloud model (Wei, 2005). Finally, the principal component of different cities is analyzed according to membership function to achieve evaluation result. The evaluation process is showed in Figure1:

Figure 1.

Evaluation model process

Selection Of Evaluation Index

The system of evaluation index in urban public transportation system should be representative, practical and measurable. This paper refers to the current situation of public transportation system in small and medium sized cities, in which the public transportation system evaluation index is distinguished into two kinds. According to the evaluation index level established in Figure 1, a hierarchical set of factors is founded = {U₁, U₂},and U₁ = {U₁₁, U₁₂, U₁₃, U₁₄}, U₂ = {U₂₁, U₂₂, U₂₃, U₂₄} (U₁:Wire mesh rationality index set; U₂:Service level indicator set).